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Breast cancer intratumor heterogeneity, progression and metastasis

We collaborate with numerous computational biologists and biostatisticians to develop new algorithms, and apply current algorithms, to develop hypotheses from large data that can be tested in the wet lab. Examples of this include a new time-dependent lasso regression method for identifying changes in proteomic data (a), a novel method to deconvolute epigenomic data and ascribe transcription to individual cell types (b), statistical methods based upon pointwise mutual information for understanding intratumor heterogeneity (c-d), comparison of current RNA fusion detection algorithms (e), development of a computational resource that holds all TCGA data (f), and use of causal discovery for understanding breast cancer outcomes (g-h).